In signal processing, quantization is a process of mapping input values to a finite set of discrete values. Satellite navigation (e.g., Global Positioning System, or GPS) receivers typically use relatively crude quantization processes to minimize processing complexities. Commercial receivers, for example, may use 1-bit (or 2-level) quantizers that are configured to map input values to two discrete values. Quantizers with slightly higher resolutions (e.g., 1.5-bit, or 3-level quantizers capable of mapping input values to three discrete values) may be used in receivers that are configured to provide better conversion gain against certain waveform types.
Receivers that are designed to operate with anti-jam functionalities typically use much higher resolution processing to provide higher levels of interference mitigation. After the higher resolution processing, the high-resolution signal may be converted to a crude 2 or 3-level quantization to interface with satellite navigation receivers. For receivers that perform time domain anti-jam processing, this conversion process may be straightforward. However, if transform-based (e.g., fast Fourier transform, or FFT-based) interference mitigation techniques are used, an inverse transform function must be performed prior to the quantization process. Performing an inverse transform function on a high-resolution signal is complicated and time-consuming.